1. Technical Field
The present invention relates generally to power/performance management and measurement in processing systems, and more particularly, to a power management system and method that utilize activity factor headroom to improve processing performance.
2. Description of the Related Art
Computer systems are increasingly employing budgetary power management. Notebook computers, which must control energy usage to provide predictable battery life and to extend battery life, employ power management that scales system performance in accordance with those needs. Large scale rack server systems, in which maximum system performance is often dictated by power supply capability and/or cooling capability and sometimes facility and customer energy usage specifications, employ power management that throttle system performance so that operating energy usage requirements are met. Typically, the power management is provided by techniques such as dynamic voltage and frequency scaling (DVFS), which is typically a change in processor operating frequency and voltage consistent with a measured power consumption (which may be predetermined or dynamically measured). Groups of processors can be controlled by DVFS to meet a group power budget, for example, in the large-scale rack server systems mentioned above.
In present-day processors, which are typically complementary metal-oxide semiconductor (CMOS) or dynamic circuit designs, energy usage is a function of not only the voltage and frequency supplied to the processing device(s), but are also a function of how the operating workload is using the processing device(s). The power consumption of a processor includes both static power and dynamic power. The dynamic power of a processor can be modeled as P=ACV2F, where F is the processor clock frequency, V is the core voltage, C is a lumped capacitance representing all of the switching nodes and A is an activity factor that relates the relative amount of switching events taking place over a given interval. A is strongly dependent on the workload being executed by the system, especially in present-day processors that include multiple cores and multiple functional units in each core, and for which utilization may vary widely by process. For example, a workload that includes no mathematically intensive applications at all might never use available floating-point units and a workload that is mathematically intensive may use the floating-point units, but only infrequently use processor bus interfaces. Other worst-case workloads may use all functions units to the same degree.
Because some workloads have a higher energy usage for a given operating point, the system must be designed (and power-managed) in order to meet system energy usage constraints under all possible workload conditions. Typically, a system's voltage/frequency operating point(s) are determined by a worst-case workload scenario, obtained by system profile tests. The voltage and frequency of the processor(s) are adjusted to set an energy usage point that meets the required power budget or other desired performance criteria such as thermal energy production for worst-case workload and operating conditions. Otherwise, the system could exceed the power consumption budget or thermal limits and potentially shut down or fail.
However, such power management does not provide the maximum possible performance for an arbitrary workload at a given operating point, since using a worst-case workload to determine the voltage/frequency operating point by necessity indicates that all other workloads operated at the same operating point will have available headroom for improved performance. For any real-world workload that does not match the worst-case workload, it is possible that the voltage/frequency operating point could be raised without violating the power management constraints set on the system. Therefore, performance of such systems could be improved over present levels, while still meeting the system power management constraints. The additional capacity available for such workloads due to a lower activity level compared to the worst-case workload activity level, at any given operating point, is referred to herein as activity factor headroom.
It is therefore desirable to provide a method and system for using the activity factor headroom to improve processing system performance.